TY - JOUR
T1 - Cost-effective condition monitoring for wind turbines
AU - Yang, Wenxian
AU - Tavner, Peter J.
AU - Crabtree, Christopher J.
AU - Wilkinson, Michael
N1 - Funding Information:
Manuscript received December 5, 2008; revised September 3, 2009. First published September 22, 2009; current version published December 11, 2009. This work was supported by the U.K. Engineering and Physical Sciences Research Council Supergen Wind Program EP/D034566/1. W. Yang is with the New and Renewable Energy Centre, NE24 3AG Blyth, U.K. P. J. Tavner is with the School of Engineering and Computing Sciences, Durham University, DH1 3LE Durham, U.K. (e-mail: Peter.Tavner@durham. ac.uk). C. J. Crabtree is with Durham University, DH1 3LE Durham, U.K. M. Wilkinson is with Garrad Hassan, BS2 0QD Bristol, U.K. Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIE.2009.2032202
PY - 2010/1/1
Y1 - 2010/1/1
N2 - Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes aWTcondition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform- based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from director indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical faultlike perturbations were successfully detected when applied to the test rig.
AB - Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes aWTcondition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform- based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from director indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical faultlike perturbations were successfully detected when applied to the test rig.
KW - Wind turbines
KW - Condition monitoring
KW - Induction generator
UR - http://www.scopus.com/inward/record.url?scp=72749084177&partnerID=8YFLogxK
U2 - 10.1109/TIE.2009.2032202
DO - 10.1109/TIE.2009.2032202
M3 - Article
AN - SCOPUS:72749084177
VL - 57
SP - 263
EP - 271
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
SN - 0278-0046
IS - 1
M1 - 5256318
ER -